Nearly everyone has experienced a hard time buying comfortable shoes. This statement was true three months ago and it’s even more apparent today given the global pandemic we’re experiencing. Retail locations are currently shut down with both sides of the transaction feeling the effects. With no physical presence these days, the world of shoe shopping has turned entirely to e-commerce.
This forced change in both buying and selling behavior has brought on unexpected challenges; inconsistent shoe sizes being the biggest obstacle for customers.
An incorrect fitting shoe will not be comfortable, it really is as simple as that. This leads to customers playing the guessing game where they purchase multiple sizes and brands online for delivery, select which one they like the most (or sometimes none at all), and return the rest - typically free of charge. This eats through profits and isn’t a feasible business model.
As a footwear researcher, comfort is something I think about a lot since it's an inherently important aspect of shoes. Comfort has a broad meaning depending on who you ask though.
The simplest definition of comfort is the absence of discomfort. Discomfort in shoes can be caused by many different factors: shoes are too heavy, feet get wet or cold, a sole is slippery, a stitch pressing on a pinky toe, the sole is too hard, shoes are too narrow or too roomy, and so on. So of course, comfort matters, no one wants to wear uncomfortable shoes. But what is the most important feature of comfort? Fit, which at a basic level is dictated by foot size and shape.
Through the work my company has done, we’ve amassed a database of over five million foot scans and there’s a very apparent trend being overlooked by most of the footwear industry. There’s a large variation of overall foot dimensions for each length grouping - forefoot width, instep height, heel width, etc.
If more footwear brands were to take this information into account in R&D then they could offer a wider range of length and width combinations; potentially capturing more customers in the process (we review why multiple sizes matter in greater detail in a research report). In most cases, shoppers can find a comfortable pair of shoes if they try on at least five pairs, testing multiple widths and brands. While this is a reasonable way of finding the right shoes in a store, it is all but impossible when buying shoes online.
In fact, our database shows the labeled size of a shoe is a very poor indicator of the actual size. Brands’ online sizing charts reveal large differences between their definitions of US shoe sizes. For instance, Under Armour’s men’s size 11 is 290mm, whereas Nike’s is 279mm. Or Adidas women’s size 9 is 255mm, versus Nike at 262mm.
We’re seeing retailers successfully pivot sales strategies and power their e-commerce channels right now by truly leveraging data and machine learning; tapping into algorithms that let them take a customer’s existing foot profile and provide recommendations based on purchases by customers with similar foot dimensions. Keeping the subjective nature of fit in mind, they can even show the percentage of customers that purchased a smaller (if they prefer tight fit) or larger size (if they prefer loose fit).
Given the information my company gathers, we’re in a unique position to study new aspects of footwear fit in methods that were unheard of 10 years ago. As companies begin to envision stores as fulfillment centers, it’s imperative they have the correct systems in place - legacy systems were not designed for a true omnichannel operation! Retailers and footwear brands alike need to find ways to capture and utilize customer data. It will make for a more well-rounded omnichannel sales strategy and lead to a happier customer with a comfortable fitting shoe.